Progression of destruction and tissue fibrosis due to chronic inflammation in some organs are known to carry a risk of cancerogenesis. Assessment of a stage of tissue fibrosis is of great importance in order to find a phase of the progression of a lesion and, further, to determine the risk of the cancerogenesis.
Chronic hepatitis is known as a disease which assessment of the stage of fibrosis of the tissue is of importance. As a method to assess the stage of tissue fibrosis, there is histopathological diagnosis. In histopathological diagnosis, a pathologist visually diagnoses a structural disorder due to the fibrotic tissues. Generally, New Inuyama Classification is used for a diagnosis of the stage of fibrosis of a liver tissue. According to New Inuyama Classification, the stage of fibrosis is classified into four stages of F1 to F4. In detail, the stage of fibrosis is classified into: no fibrosis (F0), peripheral expansion of fibrosis (F1), formation of fibrous cross-linking (F2), formation of the fibrous cross-linking associated with a strained lobule (F3), and cirrhosis (F4). However, since such classification is subjectively made by the pathologist using a pathology sample based on his/her own knowledge and experience, diagnosis according to the classification requires certain proficiency.
Also, in order to assess the stage of fibrosis, there is a method, by processing an image of the pathology sample stained by a stain such as Sirius red and the like for staining a collagenous fiber, to identify an area of the collagenous fiber and to calculate an area occupancy rate of the collagenous fiber (for example, see Non-Patent Document 1). The reason focusing on the collagenous fiber is that it has become known that, with the progression of the stage of fibrosis, the area occupancy rate of the collagenous fiber increases in the tissue. The method according to Non-Patent Document 1, by using a threshold interactively determined by the operator for each of values of RGB (Red, Green, Blue) components and values of HSV (Hue, Saturation, Value) components of the image of the stained sample, the area of the collagenous fiber is extracted. Then, from the extracted area of the collagenous fiber, collagenous fibers forming the blood vessel and the capsule that are irrelevant to the collagenous fiber associated with fibrosis due to a lesion are manually eliminated by the operator. Such a manual operation is troublesome and has a risk of variation in accuracy of calculation of the area occupancy rate of the collagenous fiber between operators.
As such, there is suggested an image processing apparatus capable of identifying a blood vessel area by appropriately distinguishing it from other areas (for example, see Patent Document 1). The image processing apparatus described in Patent Document 1 may detect an appearance pattern of an elastic fiber near a bright area in the image of the sample and, based on a result of the detection, identify an area including the bright area as the blood vessel area.